Optimal Design of IPMSM for Fuel Cell Electric Vehicles Using Autotuning Elliptical Niching Genetic Algorithm

被引：29
作者：
Kang, Young-Rok [1 ]
Son, Ji-Chang [1 ]
Lim, Dong-Kuk [1 ]
机构：
[1] Univ Ulsan, Sch Elect Engn, Ulsan 44610, South Korea
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
新加坡国家研究基金会;
关键词：
Autotuning niching genetic algorithm (ANGA); fuel cell electric vehicle (FCEV); interior permanent magnet synchronous motor (IPMSM); multimodal; niche; pattern search method (PSM); MOTOR;
D O I：
10.1109/ACCESS.2020.3004722
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To find multimodal solutions for the optimal design of an interior permanent magnet synchronous motor (IPMSM) for fuel cell electric vehicles, an autotuning elliptical niching genetic algorithm is proposed. With conventional autotuning niching genetic algorithms, some peaks are difficult to find because of a circular niche region. The proposed algorithm solves this problem by introducing an elliptical niche. The superior performance of the proposed algorithm is verified using test functions, and it is applied to the optimal design of an IPMSM for fuel cell electric vehicles.
引用
收藏
页码：117405 / 117412
页数：8
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